For unsupervised learning, self-supervised learning (SSL) methods have been proposed such as COLA[1]} for general-purpose representations and Fonseca et al.[2]} for SER.
SSL models are specifically proposed for speech representations, including Wav2Vec 2.0[3]}, PACE+[4]}, and TRILL[5]}.
In particular, Wav2Vec 2.0 was fine-tuned on the automatic speech recognition (ASR) task and provided state-of-the-art performance, and it has also been used in non-ASR application studies[6]}.
